Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/www2009/paper/175> ?p ?o. }
Showing items 1 to 8 of
8
with 100 items per page.
- 175 type InProceedings.
- 175 label "Web Image Retrieval ReRanking with Multi-view Clustering".
- 175 sameAs 175.
- 175 abstract "General image retrieval is often carried out by a text-based search engine, such as Google Image Search. In this case, natural language queries are used as input to the search engine. Usually, the user queries are quite ambiguous and the returned results are not well-organized as the ranking often done by the popularity of an image. In order to address these problems, we propose to use both textual and visual contents of retrieved images to reRank web retrieved results. In particular, a machine learning technique, a multi-view clustering algorithm is proposed to reorganize the original results provided by the text-based search engine. Preliminary results validate the effectiveness of the proposed framework.".
- 175 hasAuthorList authorList.
- 175 isPartOf proceedings.
- 175 keyword "Poster Session".
- 175 title "Web Image Retrieval ReRanking with Multi-view Clustering".